Resource monitoring has formed part and parcel of the modern computer driven control system. The modern computer driven control system includes a multiplicity of different sensors and sub-systems independently operating in concert to achieve an end result such as the production of a product. Data generated by the sensors in response to sensed conditions can be passed to the sub-systems for use in command and control decision-making, whether automated or manual. The sub-systems, in turn can produce additional data not only in respect to environmental conditions sensed by the sensors, but also in respect to the performance of the sub-systems. Of course, different sub-systems can share sensed data amongst each other in parallel or sequence depending upon the architecture of the control system.
Integral to managing a control system of multiple different sub-systems is the timely receipt of monitored data from different resources in each of the sub-systems. The more quickly monitored data can be received by a monitoring application, the more quickly the monitored data—whether raw or in reduced form—can be presented to an operator for command and control decision making. Accordingly, oftentimes, a “fast mode” can be provided through a monitoring application in response to the activation of which monitored data in the monitoring application can be updated at a faster rate. Yet, at times when a faster data-update rate is not required, the “fast mode” can be de-activated. So popular has the “fast mode” become in the modern control system architecture, some sub-system keyboards now include a hardware switch onboard to toggle the activation and de-activation of a “fast mode” for a monitored resource.
In an architecture where a single application monitors a set of monitored resources amongst the different sub-systems, the rate at which the monitored data depends solely on the speed at which the application can receive and process the monitored data. However, where multiple different and independently operating applications monitor the same monitored resource shared amongst the multiple different independently operating applications, the data rate of delivery of monitored data to different ones of the monitoring applications can depend on the processing ability of the shared resource to deliver the monitored data to the different monitoring applications. To the extent that too many monitoring applications request a high rate of data delivery of monitored data at once, the shared resource can become overtaxed requiring a reduction in data rate for the delivery of monitored data over all. Yet, serving monitored data at too slow a data rate can inhibit the timely delivery of the monitored data to a monitoring application thus defeating the ability of an operator to effectively respond to the late arriving monitored data.